ex_rSSR

Example output from the `renorm_SSR()` function, calculating the
renormalized sum of squares for the "survival" data found in `time_test`.

datasets

Analyze telemetry datasets generalized to allow
any technology. The filtering steps check for false positives caused by
reflected transmissions from surfaces and false pings from other noise
generating equipment. The filters are based on JSATS filtering algorithms
found in package 'filteRjsats' <https://CRAN.R-project.org/package=filteRjsats>
but have been generalized to allow the user to define many of the filtering
variables. Additionally, this package contains scripts used to help identify
an optimal maximum blanking period as defined in Capello et al (2015)
<doi:10.1371/journal.pone.0134002>. The functions were written according to
their manuscript description, but have not been reviewed by the authors for
accuracy. It is included here as is, without warranty.

Taylor Spaulding

telemetR

Filter and Analyze Generalised Telemetry Data from Organisms

ex_rSSR function

## `ex_rSSR`
A data frame with 100 rows and 5 columns:<dl>
 <dt>fish_type</dt>
<dd>Generally a strain, run, and species of fish (e.g.
 Nimbus Fall Chinook = Fall-run Chinook Salmon from Nimbus Hatchery)</dd> <dt>mbp_n</dt>
<dd>The maximum blanking period (in seconds) used to create a
 set of events</dd> <dt>SSR</dt>
<dd>The sum of squared residuals between this `mbp_n` and the next</dd> <dt>n</dt>
<dd>the total number of events created with this `mbp_n`</dd> <dt>rSSR</dt>
<dd>the renormalized sum of squared residuals between this `mbp_n`
 and the next</dd>
</dl>

Format

Example Renormalized Sum of Squares — ex_rSSR

## `ex_rSSR`
A data frame with 100 rows and 5 columns:<dl>
 <dt>fish_type</dt>
<dd>Generally a strain, run, and species of fish (e.g.
 Nimbus Fall Chinook = Fall-run Chinook Salmon from Nimbus Hatchery)</dd>

 <dt>mbp_n</dt>
<dd>The maximum blanking period (in seconds) used to create a
 set of events</dd>

 <dt>SSR</dt>
<dd>The sum of squared residuals between this `mbp_n` and the next</dd>

 <dt>n</dt>
<dd>the total number of events created with this `mbp_n`</dd>

 <dt>rSSR</dt>
<dd>the renormalized sum of squared residuals between this `mbp_n`
 and the next</dd>


</dl>

ex_rSSR: Example Renormalized Sum of Squares

Description

Usage

Arguments

Format